AI is only as good as what it can find.
Query Quotient builds agents, RAG systems and search for teams taking AI into production. We started in search, so retrieval is where we're strongest.
- 1Ask
- 2Search
- 3Rerank
- 4Connect
- 5Answer
search_docs("enterprise churn Q3")Churn rose after the July pricing change 1. Billing tickets spiked the same week 2, from the same enterprise accounts that later churned 3.
Search and AI teams we've worked with
Same question, different retrieval.
The way you search decides what your AI can answer. Pick a problem, then switch between keyword, semantic and hybrid retrieval to see the ranking change.
Combines both, then reranks. This is what we build for production.
- queryquotient.com › services › ai-agents0.94
AI Agents
Tool-using agents built on Claude, GPT and open models that act on your own data, with guardrails, tracing and a human in the loop.
- queryquotient.com › services › applied-ai-rag0.91
Applied AI & RAG
Retrieval pipelines and evaluation sets that make an LLM answer from your documents and databases, with citations you can check.
- queryquotient.com › services › ai-search0.88
AI Search on Elasticsearch & OpenSearch
Hybrid and vector search tuned for relevance, latency and cost: the retrieval layer every agent depends on.
Illustrative relevance scores
Every layer between your data and the answer.
An agent is only as reliable as the context it's given. Most AI teams build the top layer and hope the rest holds. We build all three, so we can fix a bad answer wherever it starts.
AI Agents
Agents plan, call your tools and APIs, and hand off to a person when they are unsure.
- Tool use & MCP
- Agents that work inside your systems
- Guardrails
- Approvals, limits and safe defaults
- Tracing & evals
- Every step visible and measured
The gap between a demo and production.
Most AI prototypes impress in a meeting and fail with real users. These are the differences we close.
- Tested onDemo-grade: A handful of hand-picked questionsProduction-grade: An evaluation set, scored on every change
- RetrievalDemo-grade: Vector search onlyProduction-grade: Hybrid search with reranking
- AnswersDemo-grade: Plausible, with no sourcesProduction-grade: Grounded, with citations you can check
- When unsureDemo-grade: GuessesProduction-grade: Says so, or hands off to a person
- Cost and latencyDemo-grade: Unknown until the bill arrivesProduction-grade: Budgeted and monitored per request
- After launchDemo-grade: Quality drifts and nobody noticesProduction-grade: Regression evals and monitoring catch it
From first call to production in about three months.
Small senior teams and an evaluation-first approach. You see working software within weeks, and every stage ends with a number you can hold us to.
1Discover
1–2 weeksPick the highest-value use case, audit the data behind it and agree on success metrics and an evaluation set before any code is written.
2Prototype
2–4 weeksA working pilot on your real data, scored against the evaluation set, so the go/no-go decision rests on evidence rather than a demo.
3Productionize
4–8 weeksGuardrails, latency and cost tuning, a security review, evals in CI, and integration with the systems your team already runs.
4Operate
OngoingMonitoring, regression evals and relevance tuning as your data changes, or a clean handover with docs and training.
We don't resell a platform, so we recommend what fits. We work across Claude, GPT, Gemini, Llama, Mistral, MCP, Elasticsearch, OpenSearch, Qdrant, Milvus, Pinecone and Weaviate.
Retrieval work that moved the numbers.
All case studies- AlphaSenseFinancial intelligence
Financial document search, rebuilt for speed and relevance
- faster queries
- 90%
- faster queries
- better relevancy
- 3x
- better relevancy
- GrabJobsRecruitment
Job matching across 10M+ listings on OpenSearch
- average query
- 5ms
- average query
- lower cost
- 40%
- lower cost
- LenskartE-commerce
Personalized product discovery at scale
- conversion lift
- 300%
- conversion lift
- response time
- <100ms
- response time
Tell us what your AI needs to find.
In a free 30-minute call we will tell you honestly whether AI is the right tool, what it would take, and how we would measure success.